This article provides a complete, practical walkthrough of the Splitout Nocodb Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Advanced setup in 1-2 hours. One‑time purchase: €69.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Automating LinkedIn Lead Generation with n8n and SerpAPI: A No-Code Workflow Guide
   
   Meta Description:  
   Discover how this simple n8n workflow uses SerpAPI, OpenAI, and NocoDB to collect and enrich LinkedIn profiles based on keyword and location. Ideal for no-code lead generation and business development.
   
   Keywords:  
   n8n LinkedIn workflow, LinkedIn lead generation, SerpAPI search automation, OpenAI enrichment, LinkedIn scraper alternative, No-code automation tools, NocoDB integration, Google Search API, automate LinkedIn searches, GPT-4o workflow n8n
   
   Third-Party APIs Used:
   
   1. SerpAPI (https://serpapi.com/) – for performing Google Search queries
   2. OpenAI API (https://openai.com/) – for enriching LinkedIn data with company names and follower number parsing
   3. NocoDB API (https://www.nocodb.com/) – for storing the cleaned and enriched data into a no-code database
   
   Article:  
   Automating LinkedIn Lead Generation with n8n, SerpAPI, and OpenAI
   
   Lead generation is essential for sales teams, recruiters, marketers, and founders, but manually sourcing LinkedIn profiles based on industry or expertise—and organizing them into usable data—can be a massive time sink. That’s where automation and no-code tools come into play.
   
   This article introduces a simple but powerful n8n workflow that scrapes and compiles LinkedIn profiles based on a keyword and location using SerpAPI, enriches the data via OpenAI, and stores the results in both an Excel file and a NocoDB database for easy access and future usage.
   
   Let’s break down what this workflow does, how it works, and how you can use it.
   
   What Does the Workflow Do?
   
   This n8n workflow titled "Simple LinkedIn profile collector" automates the following steps:
   
   - Accepts search inputs such as a keyword and a geographic location.
   - Uses Google Search (via SerpAPI) to find relevant LinkedIn profiles.
   - Splits and extracts essential data from the search results such as names, profile URLs, snippets, and follower counts.
   - Uses OpenAI (GPT-4o model) to determine the company affiliation and convert abbreviated follower counts (like “3.5k+”) into actual numbers.
   - Discards all unnecessary metadata and prepares a final dataset.
   - Outputs the data into an Excel spreadsheet and stores it in a NocoDB table.
   
   The best part? It’s approachable for beginners and avoids the need for LinkedIn scraping libraries—which is often frowned upon by LinkedIn’s terms of service—by piggybacking on Google Search.
   
   The Key Components
   
   1. Manual Trigger & Parameter Set-Up  
   The workflow begins with a manual trigger and a “Set” node that allows the user to define the search criteria, such as:
   
   - Keyword: e.g., "nocode"
   - Location: e.g., "Germany"
   - Number of search results to return: e.g., 20
   - Host language and geolocation: e.g., "en" for language and "de" for Germany
   - Search engine: e.g., "google"
   - Target site: "linkedin.com/in"
   
   This user-defined data creates a custom Google search query handled safely via SerpAPI.
   
   2. SerpAPI: Controlled Google Search  
   Instead of storing or scraping pages manually, the workflow uses SerpAPI to handle the Google search request with parameters such as:
   
   - q = site:linkedin.com/in + keyword + location
   - num = number of results
   - hl = host language
   - gl = geolocation
   
   Only the organic search results are processed; this ensures the workflow extracts accurate LinkedIn profile data.
   
   3. Data Processing & Clean-Up  
   Once the search results are in, n8n splits them into individual items. Each result is passed through a mapping node to rename or extract fields such as:
   
   - Name from LinkedIn profile
   - Profile URL
   - Description snippet
   - Rich snippet details
   - Highlighted search terms
   - Follower count (raw)
   
   4. OpenAI for Enrichment  
   This is where the magic happens. Using OpenAI’s GPT-4o model, it interprets and formats:
   
   - Follower counts like "3.3k+" into real integers (e.g., 3300)
   - Company names from profile titles or snippet texts
   
   The prompt requests only the company name and follower number, discarding irrelevant information.
   
   5. Final Merge & Export  
   After enrichment and metadata removal, the results are merged into a complete data object. Two actions take place:
   
   - Excel Export: The data is saved as a downloadable Excel file.
   - NocoDB Storage: If needed, the data is pushed into a preconfigured database table, allowing long-term storage, querying, or reporting.
   
   Why Use This Workflow?
   
   ⏱️ Time-Saving:  
   Imagine manually searching Google for LinkedIn results, copying and pasting them into Excel, then analyzing company affiliations. This saves hours of manual work.
   
   🧠 Smart Enrichment:  
   Using OpenAI to extract meaningful and standardized data (like numeric follower counts) elevates this from a scraper to a true data pipeline.
   
   📂 Structured Output:  
   Whether downloading Excel outputs or storing in an online database like NocoDB, your data is clean, enriched, and ready for use in CRMs, dashboards, or outreach tools.
   
   🧩 Modular & Extendable:  
   The workflow is modular, so if your organization prefers a different database or wants to send names to Mailchimp, Airtable, or Slack—you can plug those in easily.
   
   📜 Ethical Scraping:  
   By using Google (via SerpAPI) instead of scraping LinkedIn directly, the workflow avoids many terms-of-use violations and complex scraping compliance concerns.
   
   How to Get Started
   
   1. Import the JSON into n8n.
   2. Grab a free API key from serpapi.com.
   3. Set up an OpenAI account and generate your API credentials.
   4. Create a NocoDB project and set up a matching table (optional).
   5. Run the workflow manually or schedule as needed.
   6. Download the Excel or store your data in NocoDB.
   
   Final Thoughts
   
   Lead generation doesn’t need to be complicated—and it definitely doesn’t need to be manual. By combining n8n with APIs like SerpAPI, OpenAI, and NocoDB, even non-developers can build powerful automations that rival SaaS lead scraping tools.
   
   This specific LinkedIn profile collector workflow is both a learning opportunity and a scalable business tool. It’s ideal for solopreneurs, early-stage startups, recruiters, and business developers looking for a cost-effective and ethical way to build contact lists.
   
   With just a few tweaks, you can personalize this further to fit industry-specific goals or convert it into a fully autonomous system for your sales pipeline.
   
   Ready to customize and deploy your own lead-generation engine? The tools are in your hands—with no code required.
   
   —  
   Written by your AI assistant, helping you unlock the power of automation without writing a single line of code.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.